Automatic clustering for unsupervised risk diagnosis of vehicle driving for smart road
Early risk diagnosis and driving anomaly detection from vehicle stream are of great benefits in a range of advanced solutions towards Smart Road and crash prevention, although there are intrinsic challenges, especially lack of ground truth, definition of multiple risk exposures. This study proposes...
Saved in:
Main Authors: | Shi, Xiupeng, Wong, Yiik Diew, Chai, Chen, Li, Michael Zhi Feng, Chen, Tianyi, Zeng, Zeng |
---|---|
Other Authors: | School of Civil and Environmental Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/162965 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Document clustering based on cluster validation
by: Niu, Z.-Y., et al.
Published: (2013) -
Local bounding technique and its applications to uncertain clustering
by: ZHANG ZHENJIE
Published: (2010) -
Using cluster validation criterion to identify optimal feature subset and cluster number for document clustering
by: Niu, Z.-Y., et al.
Published: (2013) -
Pairwise sparsity preserving embedding for unsupervised subspace learning and classification
by: Zhang, Z., et al.
Published: (2014) -
FEATURE SELECTION : A PREPROCESSING STEP IN DATA MINING
by: MANORANJAN DASH
Published: (2020)